The Pentagon won’t say why its targeting manual was released online

Last week without fanfare, a 230-page military document(PDF) appeared in the public domain. The document, authored in May 2016, is a comprehensive list of rules, standards, and definitions governing the heart of what the military does: picking targets, and making sure those targets are valid and within the bounds of the laws of war.

The Pentagon isn’t exactly sure how the document ended up online. On Monday, Nov. 15, the nonprofit Federation of American Scientists ran a short post on the newly public document. Entitled “Joint Chiefs Urge “Due Diligence” in Targeting the Enemy,” the post highlights the central theme of the instruction manual: attacking the wrong target in war can have negative consequences for the United States and the countries it works with. This is a simple point, repeated and clarified through page after unredacted page in great detail, setting not just the rules but the very language that America’s military uses when fighting wars and deciding which object or person to fire at.

This doesn’t govern all the rules for use of force abroad; as Steven Aftergood of the Federation writes, “The manual applies to the Department of Defense and the military services. It does not govern lethal operations by the Central Intelligence Agency.” Most significantly, that means some operations, like targeted drone strikes flown for the CIA, are not governed by this manual.

What the manual does cover is almost everything else, from air forces and airfields, to the difference between a facility and an installation. There are rules for documenting what gets selected as a target, and guidelines for properly citing sources in an Electronic Target Folder, or the document used to show evidence that a given building, is, say, a cache of weapons used by an insurgent group, instead of a general store visited entirely by civilians.

The manual instructs commanders selecting targets to answer specific questions, like “How will the target system or adversary capability be affected if the target’s function is neutralized, delayed, disrupted, or degraded as planned” and “What is the expected adversary reaction to loss or degradation of the targets and target system’s functions?” In order for a target to be approved by intelligence agencies, like the CIA, NSA, the Defense Intelligence Agency (DIA), and the National Geospatial-Intelligence Agency (NGA), it has to go through vetting.

In the vetting process, an Electronic Target Folder “without minimally populated collateral damage considerations and intelligence gain/loss statements prior to vetting shall be considered incomplete and should not be vetted.” The Pentagon isn’t just about fighting wars, it’s interested in fighting them the right way, and that means checking to make sure the intelligence community, the government’s community of spooks and spies, think the target is valid, and that the commanders are planning for possible consequences from strikes or raids.

The specifics of the manual are a weird sort of niche material: the document is unclassified, so nothing inside it is regarded as a state secret, but it’s labeled For Official Use Only, a designation that signals it’s written entirely for an internal audience. And outside the Pentagon, the community of people who follow targeting rules is admittedly narrow.

Micah Zenko is one of those watchers. A senior fellow at the Council on Foreign Relations, Zenko writes and researches on the norms of war, the ways expectations shape future behaviors of nations and militaries. In 2013, the Joint Staff released the Joint Targeting publication after Zenko filed a Freedom of Information Act.

“But it’s not just operational, there’s a moral element embedded in the instruction,” says Zenko, “including why certain laws of armed conflict apply and how they apply. It’s to get everybody on the same wavelength; the interesting thing from my perspective on it being public is it also describes the process now to the general public. Most American people won’t read this or know about it, but to the extent that it’s available to the general public, that makes a difference.”

The manual appeared online in full shortly after the election. While the rules for how the Pentagon picks targets might not be every voter’s first priority, it came up on the campaign trail. On Dec. 2, 2015, then-candidate Donald Trump said, “The other thing with the terrorists is you have to take out their families, when you get these terrorists, you have to take out their families. They care about their lives, don’t kid yourself. When they say they don’t care about their lives, you have to take out their families.”

That’s a violation that goes against the Geneva Conventions, and, in March, Senator Lindsey Graham alluded to Trump’s stance when he asked Chairman of the Joint Chiefs of Staff John Dunford about the effect intentionally targeting civilians would have on the troops asked to do the targeting.

Dunford responded “those kind of activities that you’ve described, they’re inconsistent with the values of our nation and quite frankly I think it would have an adverse effect.”

Despite Dunford’s prior objections to the President-elect’s stated plans for the military, the Pentagon isn’t claiming responsibility for the release. When asked how the manual appeared online, a spokesman for the Joint Staff said the manual was prepared and reviewed for foreign disclosure release to Australia, Canada, New Zealand, the United Kingdom, who are partners with the United States in Five Eyes, an intelligence-sharing alliance. The manual was posted on the joint electronic library, a .mil-access-only website. As for how it’s public? “The Joint Staff did not publically release,” said the spokesman.

It’s possible the target was an international audience, as preparation for sharing with Five Eyes partners suggests.

“The United States is the only great power who makes its military doctrine so widely available,” says Zenko. “The French don’t, the British do on some issues but not this, obviously the Chinese and the Russians don’t.” So it’s possible that the manual was prepared for release to specific allies of the United States, and then released to a larger audience as a way to try and shape standards across the militaries of the world.

There’s also the possibility that this release is aimed, not at setting rules for the future, but showing when existing practices have been violated. Civilian appointees to the Pentagon in this administration “use normative language about the use of force,” says Zenko, with an aim to “reinforce norms about precision, discrimination, proportionality, adherence to laws of armed conflict.”

“Then if there’s a rupture in that with the next administration,” Zenko continues, “it becomes more jarring, it becomes a little harder to sustain, especially among congressional overseers.”

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EscapeYourBubble Shows You Stories From Outside Your Echo Chamber

Chrome: Before you sit down to a tense Thanksgiving dinner in an election year, take a moment to see how your family sees the world. EscapeYourBubble shows you what people on the other side of the aisle are seeing.

It’s no secret that we all live in self-reinforced echo chambers. While it’s comfortable seeing stuff you agree with, it can leave you wondering where everyone else is getting their information. To help bridge that gap, EscapeYourBubble shows you curated news articles that appeal to whichever group you’re not a part of. Right now, it lets you choose between Republicans and Democrats.

Since the articles you see are curated, you’re less likely to get wrapped up in an algorithmic circle churning out junk. The extension adds articles to your existing Facebook news feed, so you’re not overwhelmed with everything that’s made to appeal to someone else. You still get your feed, it’s just peppered with stories that other people are seeing. Stories inserted by EscapeYourBubble are also labeled with a bright pink banner so you know where it’s coming from.

The goal here isn’t necessarily to say that everything the other side says is right. However, if you want to connect with other people—and maybe even persuade them!—it helps to understand where they’re coming from. You don’t have to agree to read something.

EscapeYourBubble | Chrome Web Store

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Trump’s new tech adviser wants to gut the FCC

On Monday, President-elect Trump named two advisers to his tech policy transition team. One of those experts, director of the Public Utility Research Center at the University of Florida Mark Jamison, wrote a blog entry last month explaining his position on the FCC — namely, that the country could do without it. In his opinion, the nation should almost completely dissolve the antiquated agency and farm out many of its regulatory duties to the FTC and local officials because the telecom industry is competitive enough to require far less oversight.

"Most of the original motivations for having an FCC have gone away. Telecommunications network providers and ISPs are rarely, if ever, monopolies," he said in the post.

Given that assumption, In Jamison’s opinion, a whole agency devoted to regulating internet providers is overkill. Instead, the FTC and state authorities would handle anticompetitive conduct. Internet content competes well enough with broadcast television, so the latter don’t need regulation either. The only thing left for the FCC to handle is doling out radio frequencies, which could be done by a smaller independent agency that won’t change its priorities to sync with new Congressional members, presidents or commissioners.

We expected deregulation to be at the top of the list for the Trump administration’s tech agenda. Jamison dismissed the FCC’s work to preserve net neutrality and unlock set-top boxes as political favoritism that also coddled a cottage industry that sprung up to support those causes. Trump’s other advisor on the tech policy transition team, Jeffrey Eisenach of the conservative American Enterprise Institute, has actively crusaded against telecom regulation and net neutrality.

Even as the shadow of the Trump administration looms over the agency, which might see many of the industry and consumer protections it’s created in the last few years rolled back, the FCC has continued to work. A month ago, it passed new privacy rules protecting personal data from ISPs, which must now ask permission to monitor browsing habits. It’s also handed down judgments on Comcast ($2.3 million, charging customers for services they didn’t order) and T-Mobile ($48 million, poor disclosure of speed throttling).

Via: DSL Reports

Source: The Washington Post

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Steam’s first game awards are chosen by you

Valve doesn’t want to leave game awards to others any more. The gaming giant is introducing its first-ever Steam Awards, and it’s asking the community to decide on both the nominees and the winners. These aren’t the usual best-in-category awards, either. It wants you to nominate titles based on everything from their addictive qualities (the "Just 5 More Minutes" award) through to the best mini games ("Game Within A Game"). You’ll get experience points and badges for nominating, so you aren’t just receiving a pat on the back for your time.

The nominations are open now, and the final votes will take place alongside a winter sale in December.

Valve is pairing the awards announcement with the start of its annual Autumn Sale, which runs from now through November 29th at 1PM Eastern. There are many, many games on sale (12,841, to be exact), but there are some highlights. Games in the Batman, Civilization, Elder Scrolls, Far Cry, Grand Theft Auto, Just Cause and Street Fighter franchises are all on sale, with discounts ranging from 10 percent to 92 percent — most of those we’ve mentioned are over 50 percent. If you’re not sure who to nominate for the awards, you’ll at least have an excuse to buy some of the candidates.

Source: Steam Awards, Steam Store

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Google’s AI can translate language pairs it has never seen

Google’s AI is not just better at grasping languages like Mandarin, but can now translate between two languages it hasn’t even trained on. In a research paper, Google reveals how it uses its own "interlingua" to internally represent phrases, regardless of the language. The resulting "zero-shot" deep learning lets it translate a language pair with "reasonable" accuracy, as long as it has translated them both into another common language.

The company recently switched its Translate feature to the deep-learning Google Neural Machine Translation (GNMT) system. That’s an "end-to-end learning framework that learns from millions of examples," the company says, and has drastically improved translation quality. The problem is, Google Translate works with 103 languages, meaning there are 5,253 language "pairs" to be translated. If you multiply that by the millions of examples needed for training, it’s insanely CPU intensive.

After training the system with several language pairs like English-to-Japanese and English-to-Korean, researchers wondered if they could translate a pair that the system hadn’t learned yet. In other words, can the system do a "zero-shot" translation between Japanese and Korean? "Impressively, the answer is yes — it can generate reasonable Korean to Japanese translations, even though it has never been taught to do so," Google says.

Even the researchers aren’t 100 percent sure of how it works, because deep learning networks are notoriously difficult to understand. However, they were able to peek into a three-language model using a 3D representation of the internal data (above). When zooming in, the researchers noticed that the system automatically groups sentences with the same meanings from three different languages.

In essence, it developed its own "interlingua" internal representation for similar phrases or sentences. "This means the network must be encoding something about the semantics of the sentence rather than simply memorizing phrase-to-phrase translations," the researchers write. "We interpret this as a sign of existence of an interlingua in the network."

In one experiment, for instance, the team merged 12 language pairs into a model the same size as for a single pair. Despite the drastically reduced code base, they achieved "only slightly lower translation quality" than with a dedicated two-language model. "Our approach has been shown to work reliably in a Google-scale production setting and enables us to scale to a large number of languages quickly," the team says. Bear in mind that it only started seriously working on AI for languages a short time ago, so its rapid progress is pretty scary — especially if you’re a professional translator.

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